2013 | OriginalPaper | Chapter
A Variational Framework for Multi-region Image Segmentation Based on Image Structure Tensor
Authors : Xue-Min Yin, Ming Wei, Yu-Hua Yao, Jian-Ping Guo, Chong-Fa Zhong, Zhe Zhang, Yi Wei
Published in: Advances in Image and Graphics Technologies
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper presents a variational framework for multi-region image segmentation method based on image structure tensor. The multi-region segmentation is addressed by employing the multiphase level set functions with constraint. The image feature is extracted by using the image structure tensor. The coupled Partial Differential Equations (PDE) related to the minimization of the functional are considered through a dynamical scheme. A modified region competition factor is adopted to speed up the cure evolution functions, it also guarantees no vacuum and non-overlapping between the neighbor regions. Several experiments are conducted on both synthetic images and natural image. The results illustrate that the proposed multi-region segmentation method is fast and less sensitive to the initializations.